Population-wide coronaviruses are common in animals, providing a rich source of epidemiologic data that can be applied to disease modeling of coronaviral infectionInfection in humans. We modeled heterogeneous SARS-CoV-2 exposure in a naturally infected human population using a range of high-risk (inoculation and direct contact) and low-risk (inanimate fomite) exposures in a rat model of SARS-CoV-2 transmission. Using these data, we developed deterministic compartmental models in humans with the goal of predicting pandemic to endemic transitionPandemic to endemic transition dynamics of COVID-19COVID-19 in the United States. After accounting for translationally altered parameters between rat-derived data and human SARS-CoV-2 transmission, and after introducing vaccination, we arrived at a median time to endemic stability of 1437 days (interquartile range (IQR) = 749.25) with a median 15.4% of the population remaining susceptible. We extended the models to introduce successive variants with increasing transmissibility and included the effect of varying duration of immunityImmunity. Our models predicted approximate pandemic to endemic transitionPandemic to endemic transition of COVID-19COVID-19 occurring in December 2023 and were consistent with highest mean national peaks occurring in the late summer and winter. Test positivity rates in early summer and fall were lower, however reporting declined due to home testing vs. reported testing with a healthcare provider. Rates of vaccine uptake declined; however, our models indicated that vaccination combined with natural immunityImmunity maintained a lower prevalence of infectionInfection than natural infectionInfection.